Social Epidemiology Research Paper

1. Rationale For A Social Epidemiologic Approach To Disease Prevention

1.1 Magnitude Of The Disease Problem

Consideration of social factors in efforts to prevent disease is suggested by the sheer magnitude of many diseases (including coronary heart disease, cancer of various sites, arthritis, mental illness, diabetes, and stroke). While a one-to-one approach to diseases of great prevalence clearly is of value to patients, families, and friends, it does little to alter the distribution of disease in the population because new people develop disease even as sick people are treated and cured. Thus, an individual approach exhausts substantial medical care resources but does little to address those social and environmental factors that have initiated the problem. In this circumstance, an environmental approach to prevention is clearly more efficient.

1.2 The Patterning Of Disease Rates

The continual swell of new ‘at-risk’ people in the population leads to the second reason for considering social factors in disease prevention research and programs: groups often have a characteristic pattern of disease over time even though individuals come and go from these groups. This pattern indicates that there may be something about groups that either promotes or discourages disease among individuals in those groups. One example of patterning of disease rates is provided by the case of coronary heart disease (CHD). CHD rates are far higher in the US than in Japan.Yet when men from Japan immigrate to the US, their CHD rates are five times higher compared to those in their country of origin. This increase in rate is observed even after account is taken of such CHD risk factors as blood pressure, cigarette smoking, diet, and serum cholesterol levels. It seems reasonable to suggest that something about the environment of the US causes people who settle here to slowly adopt the endemic rates of disease in the US (Marmot and Syme 1976). This example of patterned consistency of disease rates across geography, social, and cultural groups emphasizes the potential importance of environmental factors in the study of disease etiology. In consequence, a considerable amount of research has been done in hopes of identifying social and environmental factors so that interventions might be developed to prevent or control disease.

1.3 Difficulties In Changing Behavior

A third reason for the consideration of social factors in disease prevention is that the prevention of many diseases requires that people change their behavior. To prevent these diseases, people are increasingly asked to begin to do things they have not done previously, to stop doing things they have been doing for years, and to do more of some things and less of others. This behavioral approach to disease prevention contrasts with programs that attempt to do something ‘to’ people. While some diseases and conditions can be treated best by injection, surgery, or other nonbehavioral manipulations, most diseases of concern today cannot. Diseases such as cancer, diseases of the cardiovascular system, cirrhosis, and some respiratory diseases to a greater or lesser degree are associated with particular behaviors and hopefully can be prevented or treated by behavior change (Ferguson 1998, Canada Department of Health and National Welfare 1974).

It is one thing to identify a risk behavior and another thing to insure that people will actually change that behavior. While there certainly are examples of successful programs to change behavior, the evidence suggests that behavior change is a very difficult and complex challenge (Syme 1986). While many different factors need to be considered in helping people change their behavior, one factor rarely considered is that of the environment. It is difficult to expect that people will change their behavior easily when many forces in the social, cultural, and physical environment conspire against such change (Leventhal and Cleary 1980). If successful behavior-modification programs are to be developed to prevent diseases, more attention will need to be given not only to the behavior and risk profiles of individuals, but also to the social environment within which people live.

2. Social Factors And The Incidence Of Disease

2.1 Personal Dispositions

Since about 1970, research evidence has accumulated regarding the role of many social factors in disease etiology. While most of this work has been done in reference to coronary heart disease, other diseases also have been studied. Early studies emphasized the role of mobility and Type A behavior pattern as risk factors for disease, but subsequent research did not uniformly confirm these findings. A new generation of research has emerged from this early work that focuses on particular components of the behavior pattern such as antagonism, resentment, time urgency, anger, need for control, self-involvement, self-esteem, and hardiness (Syme 1992). The most impressive and consistent findings from this body of research have been on the concept of hostility which has been shown to be related to coronary heart disease in a wide variety of studies (Miller et al. 1996). Other research noted below has a limited sense of control to health, with other dispositions such as optimism and negative affect receiving increased attention.

2.2 Social Support And Social Connection

Historically, one of the earliest areas of interest in the social patterning of disease has been the beneficial effect of marital status on health. While this research area has yielded interesting results, it also has branched out to new research areas on social support and social connection.

It has been known for many years that people who are not married—whether single, separated, widowed, or divorced—have higher mortality rates than married people. Not only is having a spouse beneficial to health, but loss of spouse to death is particularly detrimental. Common to marital status research are the themes of social support and social connection. In an influential article Cassel (1976) pointed out that lack of social connection, such as disruption of marriage or moving to a new social setting, was associated with a wide range of disease outcomes. According to Cassel’s hypothesis, the essential element in these situations was lack of social connection or support. In the absence of social connections a person becomes generally susceptible to illness, the specific type of which was determined by that person’s particular risk situation. The concept of social support subsequently was studied in a large community sample in Alameda County, California (Berkman and Syme 1979), in Tecumseh, Michigan (House et al. 1982), and in eastern Finland (Kaplan et al. 1988). In these studies, a strong association between networks and mortality has been observed for all causes of death for men, but only sometimes for women. These findings persisted even after account was taken of a broad range of other risk factors such as age, obesity, smoking, physical activity, health practices, education, and family history.

Several reviews (Broadhead et al. 1983, House et al. 1988, Berkman and Glass 2000) have critically assessed this literature and have concluded that something of importance is going on but that the precise elements of this ‘something’ are not yet clear. One possible explanation for the inconsistent pattern of findings may be that a few simple questions about relationships (e.g., about marriage, clubs, and number of friends) may be enough to separate those with ties from those without ties in large, urban areas like Alameda County, but that these questions are not precise enough in smaller, more rural communities, or for women. Further work will be necessary to better define the importance of various dimensions of social networks and social support for health and wellbeing.

2.3 Socioeconomic Status

Socioeconomic status has the effect of grouping individuals and of nesting them within geographic, social, and occupational environments. Obviously, not all environments are equal. They are more or less desirable places to live or work for a variety of reasons: more or fewer public and private resources; better or poorer housing and infrastructure; higher or lower levels of social capital; and more or less evenly distributed wealth. These environmental differences are patterned by socioeconomic status. Yet, as noted above, socioeconomic status is often treated as if it was a characteristic of individuals. Poverty, richness, and social status are qualities of environments as well as of people.

Evidence that area socioeconomic status has an independent relationship with mortality, over and above individuals, has emerged in the 1990s. Haan and colleagues showed that residents in a federally designated poverty area experienced elevated age, race, and sex-adjusted mortality over a follow-up period compared to residents of a nonpoverty area (Haan et al. 1987). In this study, the heightened risk of death persisted after adjustment for a wide range of demographic, behavioral, social, psychological, and health characteristics. These researchers concluded that the social environment contributed to the association between low socioeconomic status and excess mortality, independent of individual factors. Recently, other analyses have supported these results on a nationwide scale (Anderson et al. 1997).

Further support for this observation comes from England, where Blaxter (1990) investigated a wide variety of health outcomes in manual and nonmanual workers living in different types of areas. The interaction between social class of area of residence and individual social class characteristics was also reported by Yen and Kaplan (Yen and Kaplan 1996), and Shouls and colleagues (Shouls et al. 1996). Both studies found that poverty area of residence, together with individual characteristics, affect illness and adoption of risk behaviors.

Another approach to the study of area quality, one that focuses on economic patterns, involves attention to equality of income distribution, a concept which has no equivalent measure at the individual level. In recent years, evidence has accumulated to suggest that within populations of developed countries, it is the relative socioeconomic position as well as the absolute level of income that is associated with health (Wilkinson 1992). Wilkinson has shown that, in a sample of industrialized countries, life expectancy increases as the distribution of income in the country becomes more egalitarian. Data from the Luxembourg Income Study revealed a correlation of 0.86 between life expectancy and the proportion of the total net income received by the least well-off 70 percent of the population. In addition, when changes in income distribution and life expectancy were compared over time, increases in equality of income distribution were associated with greater increases in life expectancy.

Two other recent studies have explored the association between income distribution and mortality and morbidity within the United States. Although these studies used different measures of income distribution, they report similar results: as the equality of the income distribution increases, the age-adjusted rates of all-cause mortality decreases. In one of these studies (Kennedy et al. 1996), similar relationships are seen between state income equality and mortality from heart disease, malignant neoplasms, cerebrovascular disease, and homicide. In the second study (Kaplan et al. 1996), strong, significant correlations are observed between greater income equality and lower rates of all-cause and age-specific mortality, other health indicators (including rates of low birth weight, violent crimes, disability, per capita expenditures on protection, sedentary behavior, and current smoking), other social indicators (proportions of people who are unemployed, proportion receiving Aid to Families with Dependant Children, and proportion without health insurance). There is considerable debate as to the interpretation of these findings regarding income inequality. Some argue that income inequality at the population level simply represents individual differences within that population and that these individual characteristics cause disease (Gravelle 1998). Others suggest that income inequality affects health because it causes individuals with low income to experience relative deprivation with resultant feelings of distrust, shame, and hostility (Kawachi et al. 1997). A third view is that income equality is a reflection of political and economic forces in the community that generate inequality and that impact the distribution of such resources as schooling, medical care, social welfare, and working conditions (Lynch et al. 2000) which, in turn, affects health and wellbeing.

Social class differences are important determinants of health. Further research to better understand the meaning of social class gradients and of income inequality is important to help in the development of appropriate and effective interventions to improve health.

One of the most persistent disease patterns observed in public health research is that people in the lowest socioeconomic groups have the highest rates of morbidity and mortality. In a comprehensive review of 30 studies on this topic, Antonovsky noted the consistency of this finding dating from the twelfth century (Antonovsky 1967). Further, this differential has been observed throughout the world, regardless of whether the dominant diseases of death and disability were attributed to infectious or noninfectious causes and regardless of the specific methods used to assess socioeconomic status (Syme and Berkman 1976, Feinstein 1993).

In a massive nationwide survey of mortality in the United States, Kitagawa and Hauser (Kitagawa and Hauser 1973) found that mortality rates varied dramatically among socioeconomic groups for both men and women, whether socioeconomic status was studie in relation to education, income, or occupation: the lower the socioeconomic level, the higher the death rate. In addition, Kitagawa and Hauser found that those in lower socioeconomic groups had higher death rates for every cause of death except, among women, cancer of the breast and motor vehicle accidents. Higher rates of morbidity also have been observed among those in lower socioeconomic groups. These higher morbidity rates include virtually every disease as well as mental illnesses and conditions such as schizophrenia, depression, unhappiness, worry, anxiety, and hopelessness (Syme and Berkman 1976, Haan et al. 1989).

One problem with this observation is to identify those components of socioeconomic status that are potentially amenable to intervention. Research done by Marmot and his colleagues (Marmot et al. 1978) on British civil servants provides an opportunity to identify some of these components. These investigators have demonstrated that British civil servants in the highest grade (administrators) had the lowest rate of coronary heart disease while those in the lowest grade (mainly unskilled manual workers) had rates four times as high. After account had been taken of such coronary heart disease risk factors as serum cholesterol, cigarette smoking, blood pressure, physical activity, glucose intolerance, and social support, the differences in rate between those at the top and bottom of the graded hierarchy was reduced to three times. However, about 60 percent of the difference in coronary heart disease rates among civil service grades remained unexplained after this adjustment. More interesting is the fact that workers in professional and executive jobs (grade 2) and in clerical jobs (grade 3) have coronary heart disease rates 2 and 3.2 times as high as administrators.

Although the relation of socioeconomic position to health is not linear in the general population, since the largest differences are usually seen at the broad lower end of the distribution, the finding of Marmot and colleagues poses a challenge. While it is reasonably simple to come up with possible explanations for the fact that those at the bottom have higher rates than those at the top, these explanations do not account for the fact that those close to the top have higher rates of disease than those at the top. Factors such as inadequate medical care, unemployment, low income, racial factors, poor nutrition, poor housing, and poor education may account for higher rates of disease among those in grade 5 but they seem unlikely to explain why professionals and executives in the British civil service have rates twice as high as administrators.

These socioeconomic differences in disease are not unique to British civil servants. They have been observed in a wide variety of populations in many different countries, and are not confined to a single age group or disease entity, having been observed for many body systems—including the digestive, genitourinary, respiratory, circulatory, nervous, blood, and endocrine systems (Haan et al. 1989, Marmot et al. 1978, Susser et al. 1985)—and diseases (e.g., most malignancies, congenital anomalies, infectious and parasitic diseases, accidents, poisoning and violence, perinatal mortality, diabetes, and musculoskeletal impairments) as well as for early stages of and progression to carotid atherosclerosis (Lynch et al. 1995, Lynch et al. 1997).

A number of approaches have been taken to explain the link between socioeconomic status and disease. One possible explanation is the concept of ‘control of destiny.’ It could be postulated, for example, that the lower down one is in the socioeconomic status hierarchy, the less control one has over the factors that affect life and living circumstance. This hypothesis is very general, and it does not specify whether control involves money, power, information, prestige, experience, or something else. Over the years, many social scientists have studied different concepts related to the idea of ‘control of destiny’: mastery, self-efficacy, locus of control, learned helplessness, controllability, predictability, desire for control, sense of control, powerlessness, hardiness, competence, and so on (Syme 1989).

Research on job stress provides an example of the feasibility of intervening on ‘control.’ For many years, researchers have explored the relationship between ‘job stress’ and disease. It was only after Karasek (Karasek et al. 1981), Theorell (Theorell et al. 1984), and their associates added the idea of job latitude and discretion to that of job stress that such a link was observed. These investigators have shown in several studies that occupational stressors have consequences for health especially when workers do not have sufficient latitude and discretion for coping with these stressors. When workers have little control over work pace and methods, higher rates of catacholamines are seen as well as higher rates of mental strain, coronary heart disease, and other health problems. The implications for prevention are perhaps clearer when one is able to focus on such concepts as worker discretion, latitude, and involvement rather than broader concepts such as socioeconomic status. This focus also directs attention to the work environment and not simply to the individual worker.

2.4 Race And Ethnicity

Another pervasive and persistent patterned regularity in the study of health and disease is seen between race and ethnic groups. For example, young and middle-aged Black Americans have disproportionately high morbidity and mortality rates (Lillie-Blanton et al. 1996). McCord and Freeman (1990) have estimated that Black men living in Harlem in 1980 had less chance of surviving to the age of 65 than men in Bangladesh, and recent data from a nationwide study by Geronimus (1992) show that this situation was even worse in 1990. Geronimus and colleagues indicate that about half of the higher mortality rate in Blacks is due to poverty. Other possible explanations for the differences in mortality rate and life expectancy might include discrimination, lifestyle factors, use of medical care, and biologic differences. Exploration of the relative importance of these factors is complicated by the fact that ‘race’ is such an imprecise term. Biologically, race is an indicator of the distribution of gene frequencies across populations, but, as Susser et al. (1985) point out, this distribution of genes is deeply conflated with geographic, social class, and cultural distinctions. Many physical anthropologists prefer to dispense with the term altogether because it is so vague.

Nevertheless, race clearly has social meaning. Race has impact on life choices and opportunities, on education and employment. Race influences the social environmental conditions in which people live. And race influences how people interact with each other and this may have health consequences. In an innovative and pioneering study, Krieger and Sidney (1996) studied the consequences of racial discrimination on blood pressure in 5,115 young adults in four US cities: Birmingham, Chicago, Minneapolis, and Oakland. Eighty percent of Black men and women reported experiences of racial discrimination in seven basic life situations. Racial discrimination and internalized responses to the discrimination were associated with elevations of blood pressure. Working-class Black adults who reported no experiences of discrimination, yet said they typically accept unfair treatment as a fact of life, had systolic blood pressure 7 mm Hg higher than white adults, and had higher blood pressure than Black adults who typically challenged and reported discrimination.

Racial categories are clearly associated with differences in life expectancy, disability, cirrhosis, infant mortality, birth-weight, arthritis, diabetes, hypertension, anemia, and virtually every cause of death among adults. These are important and complex issues that deserve a high priority in our research agenda. Recent research on race, especially that focusing on Black– White differences, is providing important new findings (Geiger 1996, Fang et al. 1996, Laveist 1993). It is clear that this issue deserves serious and continued attention directed to a wider range of racial and ethnic groups.

3. Conclusion

The importance of social factors in the etiology of many diseases is becoming increasingly clear. The evidence for some factors remains tentative or unclear. Nevertheless, it is impressive that an increasingly large body of consistent findings is being generated in spite of these major methodologic problems. It may be premature to use the data emerging from this research in public health programs, but it is clear that they will be needed soon. The reason for this is that most serious diseases today are importantly influenced by the social environment. For these reasons, interventions in the social environment clearly will be necessary, and continued research on social factors therefore must become an important priority in both public health planning and program development.

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